Brightness is a fundamental quality of human vision. The mission of the National Eye Institute, and that of the SAVP program in particular, include understanding normal visual processing. Investigation of the neural mechanisms underlying brightness perception will contribute to our understanding of visual processing in general. This knowledge lays the groundwork for therapeutic interventions for disordered vision. A central problem in the study of brightness perception is understanding how the visual system separates the reflectances of objects from their illumination. These two variables are confounded since their product determines the amount of light reaching the eye from a particular surface. When the visual system is successful at separating reflectance and illumination it is said to be displaying brightness (or lightness) constancy, and perception is veridical. Perceptual errors (i.e., constancy failures) are potentially informative regarding the mechanisms underlying brightness perception, and the study of brightness illusions has historically been and continues to be a productive topic of research. While a large number of intriguing brightness illusions have been introduced, a survey of the literature reveals that the number of proposed explanations for these illusions is itself cumbersome. In addition, although phenomenal brightness demonstrations are often used to support various theories or proposed mechanisms of brightness coding, very few quantitative data are actually available to support these claims. The goal of the authors' recent research efforts, as well as the currently proposed research, is to remedy these deficiencies by investigating and modeling the spatial and temporal interactions between different areas of the visual field through the quantitative study of brightness illusions. The authors plan to continue to collect quantitative psychophysical data on brightness effects that will enlarge the quantitative database and critically test competing theories of brightness perception. In addition, these data will inform the continued development of a mechanistic model of brightness perception, the ODOG model of Blakeslee & McCourt (1999). This relatively low-level multiscale spatial filtering model has been extremely successful in simplifying our understanding of the mechanisms underlying brightness perception and in accounting for a large number of brightness effects that have previously been ascribed to a variety of different mechanisms.